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CFR.html
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<!DOCTYPE html>
<html>
<head>
<meta charset="utf-8">
<title>CFR</title>
<link rel="stylesheet" type="text/css" href="assets/scripts/bulma.min.css">
<link rel="stylesheet" type="text/css" href="assets/scripts/theme.css">
<link rel="stylesheet" type="text/css" href="https://cdn.bootcdn.net/ajax/libs/font-awesome/4.7.0/css/font-awesome.min.css">
</head>
<body>
<section class="hero is-light" style="">
<div class="hero-body" style="padding-top: 50px;">
<div class="container" style="text-align: center;margin-bottom:5px;">
<h1 class="title">
Cartoon Face Recognition: A Benchmark Dataset
</h1>
<div class="author">Yi Zheng<sup>1</sup></div>
<div class="author">Yifan Zhao<sup>2</sup></div>
<div class="author">Mengyuan Ren<sup>1</sup></div>
<div class="author">He Yan<sup>1</sup></div>
<div class="author">Xiangju Lu<sup>1</sup>*</div>
<div class="author">Junhui Liu<sup>1</sup></div>
<div class="author">Jia Li<sup>2</sup>*</div>
<div class="group">
<a href="http://cvteam.net/">CVTEAM</a>
</div>
<div class="aff">
<p><sup>1</sup>iQIYI,Inc</p>
<p><sup>2</sup>State Key Laboratory of Virtual Reality Technology and Systems, SCSE, Beihang University</p>
</div>
<div class="con">
<p style="font-size: 24px; margin-top:5px; margin-bottom: 15px;">
ACM MM 2020
</p>
</div>
<div class="columns">
<div class="column"></div>
<div class="column"></div>
<div class="column">
<a href="https://arxiv.org/abs/1907.13394" target="_blank">
<p class="link">Paper</p>
</a>
</div>
<div class="column">
<p class="link">Code</p>
</div>
<div class="column"></div>
<div class="column"></div>
</div>
</div>
</div>
</section>
<div style="text-align: center;">
<div class="container" style="max-width:850px">
<div style="text-align: center;">
<img src="assets/CFR/dataset overview.png" class="centerImage">
</div>
</div>
<div class="head_cap">
<p style="color:gray;">
The overview of dataset
</p>
</div>
</div>
<section class="hero">
<div class="hero-body">
<div class="container" style="max-width: 800px" >
<h1 style="">Abstract</h1>
<p style="text-align: justify; font-size: 17px;">
Recent years have witnessed increasing attention in cartoon media,
powered by the strong demands of industrial applications. As the
first step to understand this media, cartoon face recognition is a
crucial but less-explored task with few datasets proposed. In this
work, we first present a new challenging benchmark dataset,
consisting of 389,678 images of 5,013 cartoon characters annotated
with identity, bounding box, pose, and other auxiliary attributes.
The dataset, named iCartoonFace, is currently the largest-scale,
high-quality, richannotated, and spanning multiple occurrences in
the field of image recognition, including near-duplications,
occlusions, and appearance changes. In addition, we provide two
types of annotations for cartoon media, i.e., face recognition, and
face detection, with the help of a semi-automatic labeling algorithm.
To further investigate this challenging dataset, we propose a
multi-task domain adaptation approach that jointly utilizes the
human and cartoon domain knowledge with three discriminative
regularizations. We hence perform a benchmark analysis of the
proposed dataset and verify the superiority of the proposed approach
in the cartoon face recognition task. We believe this public
availability will attract more research attention in broad practical
application scenarios.
</p>
</div>
</div>
</section>
<section class="hero is-light" style="background-color:#FFFFFF;">
<div class="hero-body">
<div class="container" style="max-width:800px;margin-bottom:20px;">
<h1>
Dataset comparison
</h1>
</div>
<div class="container" style="max-width:800px">
<div style="text-align: center;">
<img src="assets/CFR/comparison of dataset.png" class="centerImage">
</div>
</div>
</div>
</section>
<section class="hero is-light" style="background-color:#FFFFFF;">
<div class="hero-body">
<div class="container" style="max-width:800px;margin-bottom:20px;">
<h1>
Semi-automic assembling process
</h1>
</div>
<div class="container" style="max-width:800px">
<div style="text-align: center;">
<img src="assets/CFR/semi_automic process.png" class="centerImage">
</div>
</div>
</div>
</section>
<section class="hero is-light" style="background-color:#FFFFFF;">
<div class="hero-body">
<div class="container" style="max-width:800px;margin-bottom:20px;">
<h1>
Overview of proposed approach
</h1>
</div>
<div class="container" style="max-width:800px">
<div style="text-align: center;">
<img src="assets/CFR/proposed approach.png" class="centerImage">
</div>
</div>
</div>
</section>
<section class="hero" style="padding-top:0px;">
<div class="hero-body">
<div class="container" style="max-width:800px;">
<div class="card">
<header class="card-header">
<p class="card-header-title">
BibTex Citation
</p>
<a class="card-header-icon button-clipboard" style="border:0px; background: inherit;" data-clipboard-target="#bibtex-info" >
<i class="fa fa-copy" height="20px"></i>
</a>
</header>
<div class="card-content">
<pre style="background-color:inherit;padding: 0px;" id="bibtex-info">@misc{zheng2020cartoon,
title={Cartoon Face Recognition: A Benchmark Dataset},
author={Yi Zheng and Yifan Zhao and Mengyuan Ren and He Yan and Xiangju Lu and Junhui Liu and Jia Li},
year={2020},
eprint={1907.13394},
archivePrefix={arXiv},
primaryClass={cs.CV}
}</pre>
</div>
</section>
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</body>
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